1. Field of the Invention
The present invention relates to a method for categorizing contents of a digital image, especially a method for generating a non-graphical digital image from an original digital image.
2. Description of the Prior Art
In the field of image processing, it is becoming increasingly common to choose a digital means of image capture and storage over more conventional means. One of the advantages of digital image storage is the ease for users to edit images. In other words, a digital image can be easily edited, enhanced, or copied through digital image processing. This means that new levels of simplicity and flexibility have been introduced to users in a digital image-editing environment, and accordingly, many techniques are developed and improved to add values in functionality of digital image processing.
In digital image processing, if a page needs to be captured into a digital file by an image-capturing device, such as a digital camera or a scanner, the photo on that page will be processed through a screening technique to change continuous tones into limited tone levels, such as the commonly-used halftone technique, and the other parts of the page such as lines, text and graphics will be transformed into solid spot. A screen dot is different from a pixel, used to form a photo image on a printed matter, and the size of the screen dot is proportional to tone response of pixels. Sometimes the size of a screen dot is equal to that of a plurality of pixels. The photo is screened while printing, and the screened results of each color are overlapped to form a structure of rosette and moiré. In this way, the tones of an output halftone image on the printed page can be seen equally to the continuous tones of the original photo image.
Please refer to FIG. 1. FIG. 1 shows a printed page 10 generated through digital image processing according to the prior art. The printed page 10 includes a photo 11, graphics 12, and text 13. The printed page 10 is printed according to an original page after scanned by a scanner; therefore, according to the abovementioned technique, the photo 11 of the printed page 10 is rich in moiré formed by screen dots. The graphics 12 in the printed page 10 include color marks, and graphics. The text 13 in the printed page 10 is written in neutral color (without chrominance). Please note that the definition of a graphical region here includes photos and graphics, photos in the printed page are formed by screen dots, and graphics are defined as marks, or artificially added articles with uniform and bright colors. Text includes word-lines or marks with a high luminance contrast to the background region but without any chrominance. That is “text” only means text written in neutral color, however, color text is treated as a graphic. According to the conventional technique, edges with a high luminance contrast to the background, including all the word-lines, are detected by an edge detection method. An edge is defined as a border between two sides having a luminance contrast above a luminance threshold. The conventional edge detection method utilizes an operator, given as follows, or a mask to detect whether there is an edge in a predetermined region or not:
         [                                        -            1                                    0                          1                                                  -            1                                    0                          1                                                  -            1                                    0                          1                      ]  
From this operator, we can see the (1,1) entry is −1, and the (3,1) entry is 1, which means the operator is subtracting the luminance of the left pixel from the luminance of the right pixel. Hence, one operator can only detect the luminance difference in one direction, and many operators should be applied when detecting each direction. Therefore, a lot of resources are needed and operating cost is increased accordingly. Moreover, the conventional edge detection method detects luminance of the whole printed page, including regions of middle luminance, which should not belong to the text. Please refer to FIG. 2 for an example. FIG. 2 is a drawing of the detected results including text and undesired edges according to the conventional edge detection method.
If a user wants to edit the printed page 10, for example performing an enhancement in the text 13 of the printed page 10, most methods of digital image processing according to the prior art adjust the whole image in the printed page 10 so as to get the stress effect of the text 13. But this makes the other parts in the printed page 10, such as graphics, which do not need enhancement, also be enhanced. This often creates some unexpected defects and unwanted results in exhibition of the whole image.